From the overall dataset of the Aspe database, only 3 monitoring networks are considered here.
The former two are monitoring networks considered representative of the diversity of the rivers ecosystems in continental France and operated unmodified since 2007. Pooled together, they are further referred to as “REPNET”. The RRP (perennial reference network) encompasses only minimally-impacted sites. It is operated unmodified since 2013, and further referred to as “REFNET”.
Note that one site can contribute to more than one network (true also for one survey).
A first selection is made to keep only the surveys:
Then, we selected only the surveys on the sites surveyed annually or bi-annually.
Eventually, our dataset covers 16023 surveys carried out on 1583 sites.
Figure 1.1: Venn diagram showing the number of sampling sites belonging to the reference network, to the monitoring networks and to both.
Are the sampling sites distributed evenly in space?
Figure 1.2: Map of mainland France distinguishing the reference and monitoring networks. A single point can be on both maps.
Is the sampling effort constant in time?
Figure 1.3: Annual number of sites surveyed.
On the overall dataset, the percentages of surveys with a FBI score “Good” or above (i.e. FBI < 16) is:
network | pc_good_or_better |
|---|---|
REFNET | 0.7742656 |
REPNET | 0.5504029 |
Is there a temporal trend in FBI? Do the trends differ between reference and non-refence sites?
Figure 2.1: Fish-based Index temporal trends for the sites belonging to the reference and monitoring networks. For each serie, the points and solid lines represent the annual median value across sites and the ribbon is the interquartile range.
Testing the trends significance for each of the percentiles:
Figure 2.2: Temporal trend in FBI scores annual 25, 50 and 75 percentiles across the sites for REPNET and REFNET. Solid regression lines indicate that the Mann-Kendall trend test is significant at the 5% threshold.
Figure 2.3: Temporal trend in the annual percentage of sites with ‘high’ or ‘good’ integrity according to the FBI for REPNET and REFNET. The solid regression line indicates that the Mann-Kendall trend test is significant at the 5% threshold.
NB: In the table below, trends are interpreted differently for the percentage of sites in ‘good condition’ (for which an increase indicated improvement) and for the percentiles (for which an increase indicates a degradation).
This table indicates that the slopes are not significant whatever the percentile and the network. However, for REFNET, p75 is close to the 5% threshold (p = 0.07) with an increasing trend (positive slope, i.e. degradation) and the percentage of sites in ‘good condition’ significantly decreases (negative slope, i.e. degradation). Both are congruent with a degradation trend in reference sites.
Merge the tables above.
network | period | variable | mk_pvalue | sens_slope | sig | trend |
|---|---|---|---|---|---|---|
REFNET | 2013-2023 | p25 | 0.043 | 0.0682 | TRUE | Degradation |
REFNET | 2013-2023 | p50 | 0.119 | 0.0823 | FALSE | Non-significant |
REFNET | 2013-2023 | p75 | 0.008 | 0.1225 | TRUE | Degradation |
REFNET | 2013-2023 | pc_good | 0.003 | -0.0059 | TRUE | Degradation |
REPNET | 2007-2023 | p25 | 0.837 | 0.0021 | FALSE | Non-significant |
REPNET | 2007-2023 | p50 | 0.343 | 0.0257 | FALSE | Non-significant |
REPNET | 2007-2023 | p75 | 0.837 | -0.0166 | FALSE | Non-significant |
REPNET | 2007-2023 | pc_good | 0.837 | 0.0001 | FALSE | Non-significant |
REPNET | 2013-2023 | p25 | 0.161 | 0.0328 | FALSE | Non-significant |
REPNET | 2013-2023 | p50 | 0.008 | 0.0619 | TRUE | Degradation |
REPNET | 2013-2023 | p75 | 0.008 | 0.1436 | TRUE | Degradation |
REPNET | 2013-2023 | pc_good | 0.119 | -0.0024 | FALSE | Non-significant |
Do the FBI functional metrics display temporal trends?
Figure 3.1: Temporal trend in FBI metrics annual median across the sites for REPNET and REFNET. Solid regression lines indicate that the Mann-Kendall trend test is significant at the 5% threshold.
Figure 4.1: Temporal trend in the fish populations indicators. Each point is the annual mean value of the indicator. Solid regression lines indicate that the Mann-Kendall trend test is significant at the 5% threshold. All the indicators for a given species are on a row.
The table below is intended to facilitate an interpretation of the trends in the FBI metrics by the populations trends. It is designed considering that (i) all the species are not considered in the calculation of all the metrics, (ii) the density-based metrics have to be interpreted with respect to the species densities, while the richness-based metrics have to be interpreted with respect to species occupancy rates and (iii) the species displaying a significant trend neither in density nor in occupancy rate are not likely to explain any metric trend.
REFNET | REPNET | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Richness | Density | Richness | Density | |||||||||||
Taxon | total_nb_sp | nb_rheophilic_sp | nb_lithophilic_sp | total_dens_indiv | dens_tolerant_indiv | dens_omnivorous_indiv | dens_invertivorous_indiv | total_nb_sp | nb_rheophilic_sp | nb_lithophilic_sp | total_dens_indiv | dens_tolerant_indiv | dens_omnivorous_indiv | dens_invertivorous_indiv |
Abramis brama | 🞄 | 🞄 | 🞄 | 🞄 | ↘ | 🞄 | 🞄 | 🞄 | ||||||
Alburnoides bipunctatus | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | ↗ | ↗ | ↗ | ↗ | ↗ | ||||
Alburnus alburnus | 🞄 | 🞄 | 🞄 | 🞄 | ↗ | ↗ | ↗ | ↗ | ||||||
Ameiurus melas | 🞄 | 🞄 | 🞄 | 🞄 | ↘ | ↘ | 🞄 | 🞄 | ||||||
Anguilla anguilla | ↘ | 🞄 | 🞄 | ↘ | 🞄 | 🞄 | ||||||||
Barbatula spp. | ↗ | ↗ | ↗ | 🞄 | 🞄 | 🞄 | ||||||||
Barbus barbus | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | ↗ | ||||||
Barbus meridionalis | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | ↗ | ||||||
Cottus spp. | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | ||||
Esox spp. | 🞄 | 🞄 | ↘ | 🞄 | ||||||||||
Gobio spp. | ↗ | 🞄 | 🞄 | ↘ | ↗ | ↗ | ||||||||
Lampetra planeri | 🞄 | 🞄 | 🞄 | ↗ | ↗ | 🞄 | ||||||||
Lepomis gibbosus | 🞄 | 🞄 | 🞄 | 🞄 | ↗ | ↗ | ||||||||
Leuciscus spp. | 🞄 | 🞄 | 🞄 | 🞄 | ↘ | ↘ | 🞄 | 🞄 | ||||||
Lota lota | 🞄 | 🞄 | 🞄 | ↘ | ↘ | 🞄 | ||||||||
Parachondrostoma toxostoma | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | ↘ | ↘ | ↘ | 🞄 | 🞄 | ||||
Phoxinus spp. | ↗ | ↗ | ↗ | ↗ | ↗ | ↗ | ||||||||
Rhodeus amarus | ↗ | 🞄 | ↗ | ↗ | ||||||||||
Rutilus rutilus | 🞄 | 🞄 | 🞄 | 🞄 | ↘ | 🞄 | 🞄 | 🞄 | ||||||
Salmo salar | ↘ | ↘ | ↘ | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | ||||
Salmo trutta | ↘ | ↘ | ↘ | 🞄 | 🞄 | ↘ | ↘ | ↘ | 🞄 | 🞄 | ||||
Sander lucioperca | 🞄 | 🞄 | 🞄 | 🞄 | ||||||||||
Scardinius erythrophthalmus | 🞄 | 🞄 | 🞄 | 🞄 | ↗ | ↗ | ||||||||
Squalius cephalus | 🞄 | ↗ | ↗ | ↗ | 🞄 | ↗ | ↗ | ↗ | ||||||
Thymallus spp. | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | 🞄 | ↗ | ↗ | ||||
Thirteen taxa display significant trends neither in density nor in occupancy, whatever the network. After excluding them, 21 remain, from the 34 initially considered in the calculation of the FBI. This indicates that about two third of these taxa can not be qualified as stable.
More significant trends can be observed in REPNET (18 taxa) than in REFNET (10 taxa). Significant temporal trends in the occupancy rate, related to the richness metrics, are more frequent (7 and 15 taxa, respectively for REFNET and REPNET) than in density (5 and 12 taxa, respectively). When comparing the two networks, the cross analysis reveals that only 10 taxa are likely to explain REFNET metrics trends, versus 18 for REPNET. The latter, with more sites and a longer time serie (17 years), may allow the detection of slighter trends than REFNET (13 years).
Gobio sp. is the only taxon displaying both significantly increasing and decreasing indicators (an increasing occupancy trend in REFNET but a decreasing one in REPNET). All the other taxa display either increasing or decreasing trends. Note that occupancy and density never have opposite trends, thereby confirming the classical density-occupancy relationship and the consistency our results.
Whatever the network, the Salmonids (Salmo trutta and S. salar) and the eel (Anguilla anguilla) display clear unfavourable population trends. The two taxa with the opposite trend are both Cyprinids (Phoxinus sp. and Rhodeus amarus).
Focusing on the two metrics with significant (unfavourable) temporal trends in REFNET, the trend in the number of rheophilic species is likely explained by the decreasing occurrence of the Salmodids. The trend in the density in tolerant individuals is more difficult to interpret, as none of the taxa contributing to the calculation of this metric displays clear population trend.
The density in total individuals is the only metric with a significant – unfavourable – trend in REPNET. Six out of seven taxa significantly increasing in density are Cyprinids. Lampetra planeri is the exception.
To assess the significance of a monotonous temporal trend for each sampling point, a Mann-Kendall non-parametric test is performed. Sen-Theil slope is then estimated in order to retrieve its sign. As the FBI score is a measure of degradation, both are positively correlated. Hence, if the trend is significant and the sign is positive, FBI scores tend to increase through time, reflecting a degradation of the river. On the contrary, a significant trend with a negative sign indicates an improvement of ‘river health’.
Figure 5.1: Map of the Fish-based index trends for the REPNET sites.
Degradation | Improvement | No trend | |||
|---|---|---|---|---|---|
REPNET | REFNET | REPNET | REFNET | REPNET | REFNET |
8.9% (n=124) | 15.8% (n=49) | 5.2% (n=73) | 7.1% (n=22) | 85.9% (n=1201) | 77.1% (n=239) |
Figure 5.2: Comparison between the proportions of sites in improving and degradation conditions according to the FBI, across regions (dear co-authors, note that the regions are not those of the map ! This will be fixed is this plot and the map are both kept). The regions are ordered by their proportion of sites in degradation.
Are some regions more prone than others to degradation measured by each of tthe metrics?
Figure 5.3: Map of the Fish-based index metrics trends for the REPNET sites.
Are all metrics similarly prone to temporal trends?
Degradation | Improvement | No trend | ||||
|---|---|---|---|---|---|---|
Metric | REPNET | REFNET | REPNET | REFNET | REPNET | REFNET |
nb_total_sp | 6.1% (n=85) | 8.4% (n=26) | 5.4% (n=76) | 6.1% (n=19) | 88.5% (n=1237) | 85.5% (n=265) |
nb_rheophilic_sp | 6.7% (n=93) | 10% (n=31) | 5.6% (n=78) | 6.8% (n=21) | 87.8% (n=1227) | 83.2% (n=258) |
nb_lithophilic_sp | 5.9% (n=83) | 8.4% (n=26) | 7.7% (n=107) | 7.4% (n=23) | 86.4% (n=1208) | 84.2% (n=261) |
dens_total_indiv | 7.4% (n=104) | 11.3% (n=35) | 3.4% (n=48) | 3.9% (n=12) | 89.1% (n=1246) | 84.8% (n=263) |
dens_tolerant_indiv | 8% (n=112) | 10.3% (n=32) | 5.7% (n=80) | 9.4% (n=29) | 86.3% (n=1206) | 80.3% (n=249) |
dens_omnivorous_indiv | 6.5% (n=91) | 9.4% (n=29) | 7.3% (n=102) | 11.6% (n=36) | 86.2% (n=1205) | 79% (n=245) |
dens_invertivorous_indiv | 7.1% (n=99) | 13.9% (n=43) | 8.7% (n=122) | 8.1% (n=25) | 84.2% (n=1177) | 78.1% (n=242) |